Abstr:AC7-01: Difference between revisions
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=Aerosol deposition in the human upper airways= | =Aerosol deposition in the human upper airways= | ||
==Application Area 7: | ==Application Area 7: Biomedical Flows== | ||
===Application Challenge AC7-01=== | ===Application Challenge AC7-01=== | ||
=Abstract= | =Abstract= | ||
Knowledge of deposition | Knowledge of deposition characteristics in the human airways is important when assessing | ||
the impact of inhaled | the impact of inhaled aerosols, that can be either atmospheric pollutants or aerosols | ||
intended for therapeutic purposes. | |||
Not only the total deposition, but also local depositions | |||
within individual parts of the lung are of interest. | |||
The application of computer models | |||
that are based on computational fluid dynamics for the prediction of aerosol deposition in | that are based on computational fluid dynamics for the prediction of aerosol deposition in | ||
the human airways has become very common nowadays. Despite their | the human airways has become very common nowadays. Despite their limitations, that | ||
are mainly associated to their high computational | are mainly associated to their high computational cost, CFD models offer significant advantages | ||
over ''in vitro'' / ''in vivo'' experiments. | |||
However, prior to their use CFD models | |||
need to be properly validated. This is the objective of the current application Challenge. | need to be properly validated. This is the objective of the current application Challenge. | ||
Specifically, ''in vitro'' deposition measurements using positron emission tomography (PET) | |||
have been conducted in a | have been conducted in a human-based model of the upper airways during steady-state | ||
inhalation at flow rates of | inhalation at flow rates of 15, 30 and 60 L/min. | ||
are in the transitional | The flow conditions at these flowrates are in the transitional to turbulent regime. | ||
same geometry and under the same ventilation conditions. Two sets of simulations were | CFD simulations were carried out in the same geometry and under the same ventilation conditions. | ||
performed: Large Eddy Simulations using the dynamic version of the | Two sets of simulations were performed: | ||
subgrid scale model and RANS simulations using the | Large Eddy Simulations using the dynamic version of the Smagorinsky-Lilly | ||
subgrid scale model and RANS simulations using the k-ω-SST turbulence model. In both | |||
methods, the Lagrangian approach has been adopted to track spherical particles in the | |||
airway geometry and determine regional deposition patterns. | airway geometry and determine regional deposition patterns. | ||
The methods and results described in the present Application Challenge are mainly | The methods and results described in the present Application Challenge are mainly | ||
adopted from Lizal et al. (2012) (experimental part) and Koullapis et al. (2018) (numerical | adopted from [[Best_Practice_Advice_AC7-01#lizal2012|Lizal ''et al.'' (2012)]] (experimental part) | ||
part). | and [[Best_Practice_Advice_AC7-01#koullapis2018|Koullapis ''et al.'' (2018)]] (numerical part), | ||
reporting on work carried out in COST Action MP1404 SimInhale | |||
'Simulation and pharmaceutical technologies for advanced patient-tailored inhaled | |||
medicines’. http://www.siminhale-cost.eu | |||
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{{ACContribs | {{ACContribs | ||
|authors=P. Koullapis | |authors=P. Koullapis<sup>a</sup>, F. Lizal<sup>b</sup>, J. Jedelsky<sup>b</sup>, L. Nicolaou<sup>c</sup>, K. Bauer<sup>d</sup>, O. Sgrott<sup>e</sup>, M. Jicha<sup>b</sup>, M. Sommerfeld<sup>e</sup>, S. C. Kassinos<sup>a</sup> | ||
|organisation= | |organisation=<br><sup>a</sup>Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus<br><sup>b</sup>Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic<br><sup>c</sup>Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, USA<br><sup>d</sup>Institute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany<br><sup>e</sup>Institute Process Engineering, Otto von Guericke University, Halle (Saale), Germany | ||
}} | }} | ||
{{ACHeader | {{ACHeader | ||
Latest revision as of 10:41, 21 October 2019
Aerosol deposition in the human upper airways
Application Area 7: Biomedical Flows
Application Challenge AC7-01
Abstract
Knowledge of deposition characteristics in the human airways is important when assessing the impact of inhaled aerosols, that can be either atmospheric pollutants or aerosols intended for therapeutic purposes. Not only the total deposition, but also local depositions within individual parts of the lung are of interest. The application of computer models that are based on computational fluid dynamics for the prediction of aerosol deposition in the human airways has become very common nowadays. Despite their limitations, that are mainly associated to their high computational cost, CFD models offer significant advantages over in vitro / in vivo experiments. However, prior to their use CFD models need to be properly validated. This is the objective of the current application Challenge. Specifically, in vitro deposition measurements using positron emission tomography (PET) have been conducted in a human-based model of the upper airways during steady-state inhalation at flow rates of 15, 30 and 60 L/min. The flow conditions at these flowrates are in the transitional to turbulent regime. CFD simulations were carried out in the same geometry and under the same ventilation conditions. Two sets of simulations were performed: Large Eddy Simulations using the dynamic version of the Smagorinsky-Lilly subgrid scale model and RANS simulations using the k-ω-SST turbulence model. In both methods, the Lagrangian approach has been adopted to track spherical particles in the airway geometry and determine regional deposition patterns.
The methods and results described in the present Application Challenge are mainly adopted from Lizal et al. (2012) (experimental part) and Koullapis et al. (2018) (numerical part), reporting on work carried out in COST Action MP1404 SimInhale 'Simulation and pharmaceutical technologies for advanced patient-tailored inhaled medicines’. http://www.siminhale-cost.eu
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Contributed by: P. Koullapisa, F. Lizalb, J. Jedelskyb, L. Nicolaouc, K. Bauerd, O. Sgrotte, M. Jichab, M. Sommerfelde, S. C. Kassinosa —
aDepartment of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
bFaculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic
cDivision of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, USA
dInstitute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany
eInstitute Process Engineering, Otto von Guericke University, Halle (Saale), Germany
© copyright ERCOFTAC 2019